hi
i am using the software PyCharm(2018.1) software to create ARIMA model in pyhthon
here is the model that i have created:
the error that i have got when i run the model:
any help will be appreciated
Thank you
i am using the software PyCharm(2018.1) software to create ARIMA model in pyhthon
here is the model that i have created:
def arima_Model_Static_PlotErrorAC_PAC(series, arima_order): # prepare training dataset X = series # print(X) exit() train_size = int(len(X) * 0.50) # 0.50 train, test = X[0:train_size], X[train_size:] history = [x for x in train] # make predictions print(len(history)) print(history) exit() errorList=list() expected= list() predictions = list() obs = list() for t in range(len(test)): model = ARIMA(history, order=arima_order) #exit() model_fit = model.fit(disp=False, transparams=False) yhat = model_fit.forecast()[0] #model_fit.forecast()[0] exit() predictions.append(yhat) obs = test[t] history.append(obs) expected.append(obs) errorResidualExpePred = obs - yhat errorList.append(errorResidualExpePred) print('epoch=%i, predicted=%f, expected=%f' % (t, yhat, obs)) mse = mean_squared_error(test, predictions) rmse = sqrt(mse) print(model_fit.summary()) print(rmse) return errorListi called this model as follow:
series=np.array(diffARIMA) #series=colDataSet arima_order=(11,0,32) outputResidualError=arima_Model_Static_PlotErrorAC_PAC(series, arima_order)also the values of p, d, q are well chosen by applying the following rules
- remove the seasonality
- p: lag value where PACF cuts off first, so p=11.
- d=0 because apply the ADF test test and found my series is stationary so no differentiate has been done
- q: lag value where ACF chart crosses the upper confidence interval first, so q=32
- p: lag value where PACF cuts off first, so p=11.
the error that i have got when i run the model:
Error: File "C:/109_personel/112_pyCharmArima/Presentation.py", line 296, in arima_Model_Static_PlotErrorAC_PAC
model_fit = model.fit(disp=False, transparams=False)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 946, in fit
start_ar_lags)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 562, in _fit_start_params
start_params = self._fit_start_params_hr(order, start_ar_lags)
File "C:\109_personel\112_pyCharmArima\venv\lib\site-packages\statsmodels\tsa\arima_model.py", line 541, in _fit_start_params_hr
raise ValueError("The computed initial AR coefficients are not "
ValueError: The computed initial AR coefficients are not stationary
You should induce stationarity, choose a different model order, or you can
pass your own start_params.
Finally i would like to mention that if a apply my model by selecting the following arima orderarima_order=(11,0,0) arima_order=(0,0,16)my modele is well executed
any help will be appreciated
Thank you